Combining AI-powered tools with CRM systems brings forth a data-driven approach to customer interactions and improves those interactions for both the consumer and the business. Integrating AI and automation in CRM software helps the organization take customer data to the next level with greater insights into customer behavior, needs and preferences, among other important factors.

But how did we get here? Customer engagement is at the crux of CRM. As technology has sharpened, the needs of customers have evolved. While CRM software vendors have been proponents of AI, only recently has it gained in popularity and is revolutionizing how companies and customers interact.

The original CRM systems were databases of customer information and customer interactions kept and used by accounting departments. As time went on the systems started to incorporate more features and tools for other departments, such as marketing, sales teams and customer support. However, as businesses grew so did customer expectations and the need for customer retention.

The vast amount of data generated by the CRM platform became too much for the traditional system and a new solution had to be found. This is where generative AI tools stepped in and have since changed the way CRM systems work today.

Companies today have numerous options when looking for an AI and CRM partner, including IBM CRM (IBM watsonx™ Assistant), Salesforce CRM (Einstein GPT), Hubspot CRM (ChatSpot), Freshworks (Freddy AI), Zoho CRM (Zia) and Pipedrive CRM (AI Sales Assistant).

New AI-based tools such as actionable meeting summaries, custom email templates and automated ticket routing have altered the CRM process. Other technology tools, such as using intelligent notifications provide insights into the sales pipeline. The customer experience is now at the crux of CRM and relies upon real-time data insights for the personalized and timely interactions expected by customers.

The IBM Institute for Business Value published a series of researched-backed guides called—The CEO’s guide to generative AI—on topics ranging from generative AI in cybersecurity to customer experience. The IBM Institute for Business Value has identified 3 things every leader needs to know and what they can do about it:

1. Generative AI is a seismic shock to experience.

By using customer data from all areas of a business, including sales, marketing and service functions, it can personalize a customer experience and use CRM data to its fullest potential.

What leaders can do: Aim high when it comes to your goals for using AI capabilities. Generative AI might be available to all companies. It comes down to how CEOs choose to use this capability for their business needs. Enable designers to augment content creation with generative AI and engage with AI technology. Use generative AI to make things simple by establishing use-case-specific guidelines and complement open models with an investment in proprietary data.

2. Customer trust is the new currency.

The promise of what generative AI can deliver to its customers relies on a foundation of trust from the company itself. IBM Institute for Business Value found that “80% of business leaders see explainability, ethics, bias or trust as a major concern on the road to generative AI adoption.”¹

What leaders can do: CEOs should be leading with empathy and prioritize ethical journeys. Build trust with customers by developing generative AI ethics specific to their concerns and give them a trustworthy experience that helps ensure customer satisfaction. Build generative AI into the user experience from the start, personalize marketing campaigns and direct customer outreach to further earn that trust.

3. Generative AI opens the door to reinventing the employee experience.

On average, 87% of executives expect job roles to be augmented by generative AI, not replaced. Generative AI promises to automate tasks that were previously too complicated for machines to handle. The success of a human-machine partnership is the core organizational change challenge when bringing in AI tools. CEOs need to carefully consider where to bring AI into the value chain and keep generative AI a consideration in all decision-making when it comes to employee impact and well-being.

What leaders can do: Develop a human-machine partnership from the start that can create more value than either can do alone. Make a good impression with generative AI by providing positive messaging around how it can boost employees' efficiency and productivity. Integrate the AI tools, intelligent workflows and hybrid cloud platforms in a way that engages employees to perform at the highest level and involves employees in designing the AI implementation.

Implementing AI into CRM doesn’t come without its challenges. The IBM Institute for Business Value finds that while 78% of executives say that their organization has an approach for scaling generative AI into customer and employee experiences, most are still figuring out how to ensure consistent quality. More than half (56%) report that they don’t have a process in place to review generative AI output and resolve issues. These include:

Time: The initial setup of an AI in a CRM system can be time-consuming depending on how large the organization is and what the specific needs of the business might be. For things to run smoothly in implementation, there needs to be effective team interaction. Another aspect is pricing. The more complex the AI in the CRM system the more money the company might be spending on setting up the technology.

Cybersecurity: The path to quality customer service is maintaining external data and internal data entry. Much of this is sensitive personal customer data, and it must be securely contained and only collected in accordance with the law. Customers should also know that their data is being used and stored for the intended purpose for which it was collected.

A balance between AI and human services: AI CRM can become highly automated and make for less human connection. Customers can then feel disconnected from the company and miss the personal interaction they once had with a traditional customer service department. Therefore, it’s important for the organization to remind customers that the robot is for informational assistance and won’t provide support.

The use cases for AI in CRM are vast and vary depending on what the goals of the business might be. Some important ones are:

Business intelligence: AI tools offer businesses a new approach for different areas of the business, including sales, marketing and customer service. AI provides analysis and insight into customer data that can help it make smarter long-term decisions and address customer needs.

Customer service: AI tools, such as AI chatbots can be used in a business's customer service strategy to provide quick and accurate responses to inquiries. AI-powered chatbots can enhance customer service with 24x7 support for customers' queries.

Data management: With AI in CRM it keeps customer data clean and accurate by automating the step-by-step processes, such as data entry, cleaning and enrichment. Furthermore, the AI-powered CRM can help maintain an accurate data foundation for all the AI processes spanning the business.

IT efficiency: Within CRM systems, AI, along with automation, can automate routine tasks and make processes simpler. IT departments that use AI can automate mundane tasks, such as ticket routing and diagnostics.

Marketing personalization: AI-powered CRM systems can personalize marketing material and segment customers based on incoming data points, including purchase history and engagement.

Lead management: By using AI tools for lead scoring, the business can automate the lead qualification and scoring process within the CRM system. Separately, machine learning models can gather more insight into lead characteristics and behavior further tailoring the outreach approach.

Predictive customer analytics: The data capabilities of AI are widespread, especially when it comes to AI in CRM systems. With AI, businesses can use historical data to make predictions about customer behavior and anticipate what a customer needs.

Process optimization: When AI is brought into a CRM system for process, it helps direct the operation and find inefficiencies that might have otherwise gone unnoticed. Businesses can also use AI to analyze workflows and pinpoint bottlenecks in the system.

Sales optimization: AI technology helps businesses improve their CRM sales modules by using predictive analytics to gain leads and prioritize high-value prospects. The automated workflows streamline sales processes, while the predictive analytics can help forecast customer behavior.

Customer experience is only expected to grow in necessity as hyperpersonalization is now the high bar that has been set. Every company is selling a digital product and is competing for which digital experience is the most personalized and draws the most consumer attention.

This is where generative AI steps in and promises to elevate these expectations as customers demand personalized sale offers, recommendations and unmatched customer service. As AI technology evolves, businesses can only expect more advanced AI capabilities and AI-powered tools to bolster the CRM process.

The future of AI CRM seems bright as more AI tools continue to be developed, such as voice recognition and augmented reality, among others. AI has and will continue to revolutionize the way a business engages with its customers and will evolve the way the world looks at the customer experience. Organizations that adapt and build AI into their CRM process are staying ahead of the curve and will set themselves up to thrive in the customer relationship management space.